Bidirectional LSTM network-based vehicle behavior identification method and system

The invention discloses a bidirectional LSTM network-based vehicle behavior identification method and system; the method comprises the following steps: invoking offline acquired traffic video data; detecting and tracking vehicles in the traffic video data, and extracting vehicle driving tracks; extracting features from preprocessed vehicle driving tracks, and building a training data set and a test data set; using a bidirectional LSTM recurrent neural network to make model training for the training data set, and forming a vehicle behavior identification model; inputting the test data set intothe vehicle behavior identification model to make precision assignment; inputting the traffic video data acquired online in real time in the vehicle behavior identification model with the precision assignment, identifying vehicle behaviors, and outputting an identification result. The method uses the vehicle behavior identification model based on the bidirectional LSTM network to identify the vehicle driving tracks in the traffic video data, thus determining the vehicle driving behaviors with a high identification precision.